# Will your Doorbell Camera still recognize you as you grow old

arXiv: https://arxiv.org/abs/2308.04224 · HTML: https://mlsanity.com/paper/2308.04224/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 8 references that are in the map.
- First posted on arXiv 8 Aug 2023.

## Builds on (most cited first, 1 of 1)

- [Only a Matter of Style: Age Transformation Using a Style-Based Regression Model](https://mlsanity.com/paper/2102.02754/) (2021)

## Abstract (arXiv)

Robust authentication for low-power consumer devices such as doorbell cameras poses a valuable and unique challenge. This work explores the effect of age and aging on the performance of facial authentication methods. Two public age datasets, AgeDB and Morph-II have been used as baselines in this work. A photo-realistic age transformation method has been employed to augment a set of high-quality facial images with various age effects. Then the effect of these synthetic aging data on the high-performance deep-learning-based face recognition model is quantified by using various metrics including Receiver Operating Characteristic (ROC) curves and match score distributions. Experimental results demonstrate that long-term age effects are still a significant challenge for the state-of-the-art facial authentication method.